Here you go, with explanation in comments.
import pandas as pd
from stockstats import StockDataFrame as Sdf
data = pd.read_csv('data.csv')
stock = Sdf.retype(data)
signal = stock['macds'] # Your signal line
macd = stock['macd'] # The MACD that need to cross the signal line
# to give you a Buy/Sell signal
listLongShort = ["No data"] # Since you need at least two days in the for loop
for i in range(1, len(signal)):
# # If the MACD crosses the signal line upward
if macd[i] > signal[i] and macd[i - 1] <= signal[i - 1]:
listLongShort.append("BUY")
# # The other way around
elif macd[i] < signal[i] and macd[i - 1] >= signal[i - 1]:
listLongShort.append("SELL")
# # Do nothing if not crossed
else:
listLongShort.append("HOLD")
stock['Advice'] = listLongShort
# The advice column means "Buy/Sell/Hold" at the end of this day or
# at the beginning of the next day, since the market will be closed
print(stock['Advice'])
Answer from Vincent K on Stack OverflowGitHub
github.com › GZotin › RSI_MACD_strategy
GitHub - GZotin/RSI_MACD_strategy: Python script for trading analysis using RSI and MACD indicators.
Python script for crypto trading analysis using RSI and MACD indicators.
Starred by 22 users
Forked by 5 users
Languages Python 100.0% | Python 100.0%
Videos
07:00
Programming MACD Trading Algorithm in Python - YouTube
11:21
Python For Finance - Backtesting MACD trading strategy - YouTube
24:27
Algorithmic Trading in Python - MACD: Construction and Backtest ...
30:38
Algorithmic Trading Strategy Using MACD & Python - YouTube
03:59
Coding MACD Indicator- Python Algo Trading Course - YouTube
Medium
medium.com › @financial_python › building-a-macd-indicator-in-python-190b2a4c1777
Building a MACD Indicator in Python | by Financial Python | Medium
September 22, 2023 - In this article, we’ve coded a MACD indicator in Python using AAPL stock data with a 1-hour timeframe. We’ve also explained why the common values of 12-period and 26-period EMAs are used in MACD calculations. The MACD indicator is a valuable tool for traders and investors to identify potential trends and reversals in price movements. Feel free to adapt this code for other stocks, timeframes, or additional trading strategies.
alpharithms
alpharithms.com › home › tutorials › calculating the macd in python for algorithmic trading
Calculating the MACD in Python for Algorithmic Trading - αlphαrithms
April 10, 2023 - The Moving Average Convergence Divergence (MACD) is one of the most popular technical indicators used to generate signals among stock traders. This indicator serves as a momentum indicator that can help signal shifts in market momentum and help signal potential breakouts. Integrating this signal into your algorithmic trading strategy is easy with Python...
Medium
medium.com › @teopan00 › macd-indicator-for-algorithmic-trading-in-python-ce2833993550
MACD indicator for algorithmic trading in Python | by Theodoros Panagiotakopoulos | Medium
August 30, 2023 - Within this article, we will explore ... Convergence/Divergence (MACD). Initially, we will delve into comprehending the essence of this trading tool. Subsequently, we will proceed to apply it, creating and subsequently evaluating a trading strategy utilizing Python, thereby gauging its ...
GitHub
github.com › QuantConnect › Lean › blob › master › Algorithm.Python › MACDTrendAlgorithm.py
Lean/Algorithm.Python/MACDTrendAlgorithm.py at master · QuantConnect/Lean
class MACDTrendAlgorithm(QCAlgorithm): · def initialize(self): '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.''' · self.set_start_date(2004, 1, 1) #Set Start Date · self.set_end_date(2015, 1, 1) #Set End Date · self.set_cash(100000) #Set Strategy Cash ·
Author QuantConnect
LinkedIn
linkedin.com › pulse › python-tutorial-macd-moving-average-andrew-hamlet
Investing with Python Tutorial: MACD (Moving Average Convergence/Divergence)
February 8, 2021 - For the full article, subscribe to Investing with Python on www.andrewshamlet.net ... As of today the end code works if you use import pandas as pd import pandas_datareader.data as web stocks = ['FB'] def get_stock(stock, start, end): return web.get_data_yahoo(stock, start, end)['Adj Close'] px = pd.DataFrame({n: get_stock(n, '1/1/2016', '12/31/2016') for n in stocks}) px['30 mavg'] = px.rolling(30).mean() px ... Can you please explain ewma code.
EODHD
eodhd.com › home › using python to create an innovative trading strategy and achieve better results
Python Trading Strategy: Synergizing Stochastic Oscillator and MACD Indicator | EODHD APIs Academy
February 5, 2025 - Profit gained from the STOCH MACD strategy by investing $100k in AAPL : 313585.35 Profit percentage of the STOCH MACD strategy : 313% Code Explanation: Firstly, we calculate returns for Apple stock using NumPy’s ‘diff’ function, storing them as a dataframe in ‘aapl_ret’. We then use a for-loop to calculate returns obtained from our trading strategy, appending them to ‘stoch_macd_strategy_ret’ list.
LinkedIn
linkedin.com › pulse › python-finance-part-3-macd-henry-meier
Python for Finance Part 3: MACD
March 24, 2023 - Lets test this new strategy on volatile stocks, these work best. I'm going with Gamestop (GME) over the last 3 years. /home/bot/PycharmProjects/finance/venv/bin/python /home/bot/PycharmProjects/finance/macd.py Enter the stock ticker symbol: GME Enter the start date (YYYY-MM-DD): 2020-03-01 Enter the end date (YYYY-MM-DD): 2023-03-01 Enter the initial amount of money: 1000 [*********************100%***********************] 1 of 1 completed Buy 1010.10 shares at 0.99, balance: $0.00 Sell 0.00 shares at 0.93, balance: $934.34 Buy 883.54 shares at 1.06, balance: $0.00 Sell 0.00 shares at 0.94, bal
GitHub
github.com › Nikhil-Adithyan › Algorithmic-Trading-with-MACD-in-Python › blob › master › MACD_strategy_code.py
Algorithmic-Trading-with-MACD-in-Python/MACD_strategy_code.py at master · Nikhil-Adithyan/Algorithmic-Trading-with-MACD-in-Python
print(cl('MACD Strategy profit is {}% higher than the Benchmark Profit'.format(profit_percentage - benchmark_profit_percentage), attrs = ['bold']))
Author Nikhil-Adithyan